Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units.
| Version: | 0.3.0 |
| Depends: | R (≥ 3.2.3) |
| Imports: | Matrix (≥ 1.2.4), methods, Rcpp (≥ 0.12.3) |
| LinkingTo: | Rcpp, RcppEigen (≥ 0.3.2.3) |
| Suggests: | testthat, numDeriv, scales, knitr |
| Published: | 2016-03-15 |
| Author: | Michael Braun [aut, cre, cph] |
| Maintainer: | Michael Braun <braunm at smu.edu> |
| License: | MPL (== 2.0) |
| URL: | http://www.smu.edu/Cox/Departments/FacultyDirectory/BraunMichael |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11 |
| Citation: | sparseHessianFD citation info |
| Materials: | NEWS |
| CRAN checks: | sparseHessianFD results |
| Reference manual: | sparseHessianFD.pdf |
| Vignettes: |
sparseHessianFD |
| Package source: | sparseHessianFD_0.3.0.tar.gz |
| Windows binaries: | r-devel: sparseHessianFD_0.3.0.zip, r-release: sparseHessianFD_0.3.0.zip, r-oldrel: sparseHessianFD_0.3.0.zip |
| OS X Mavericks binaries: | r-release: sparseHessianFD_0.3.0.tgz, r-oldrel: sparseHessianFD_0.3.0.tgz |
| Old sources: | sparseHessianFD archive |
| Reverse suggests: | bayesGDS |
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